This paper presents an exercise of specification of key terms in the context of my doctoral research, which investigates the processes of communication, relationships and representations in the context of a new current of African immigration in Argentina, specifically in the cities of Buenos Aires and La Plata. The aim is to problematize some categories and concepts attending to clarify its definition for our study and in the same process, contribute to the shaping of the communicational perspective we propose. This implies putting in dialogue formative experiences of the Doctorate in Communication (FPyCS, UNLP).

Shortly after the seminal paper “Self-Organized Criticality: An explanation of 1/fnoise” by Bak et al. (1987), the idea has been applied to solar physics, in “Avalanches and the Distribution of Solar Flares” by Lu and Hamilton (1991). In the following years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into the numerical SOC toy models, such as the discretization of magneto-hydrodynamics (MHD) processes. The novel applications stimulated also vigorous debates about the discrimination between SOC models, SOC-like, and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC studies from the last 25 years and highlight new trends, open questions, and future challenges, as discussed during two recent ISSI workshops on this theme.

Studies of complexity in extended dissipative dynamical systems, in nature and in laboratory, require multiple approaches and the framework of self-organized criticality (SOC) has been used extensively in the studies of such nonequilibrium systems. Plasmas are inherently nonlinear and many ubiquitous features such as multiscale behavior, intermittency and turbulence have been analyzed using SOC concepts. The role of SOC in advancing our understanding of space and laboratory plasmas as nonequilibrium systems is reviewed in this article. The main emphasis is on how SOC and related approaches have provided new insights and models of nonequilibrium plasma phenomena. Among the natural plasmas the magnetosphere, driven by the solar wind, is a prominent example and extensive data from ground-based and space-borne instruments have been used to study phenomena of direct relevance to space weather, viz. geomagnetic storms and substorms. During geomagnetically active periods the magnetosphere is far from equilibrium, due to its internal dynamics and being driven by the turbulent solar wind, and substorms are prominent features of the complex driven system. Studies using solar wind and magnetospheric data have shown both global and multiscale features of substorms. While the global behavior exhibits system-wide changes, the multiscale behavior shows scaling features. Along with the studies based on observational data, analogue models of the magnetosphere have advanced the understanding of space plasmas as well as the role of SOC in natural systems. In laboratory systems, SOC has been used in modeling the plasma behavior in fusion experiments, mainly in tokamaks and stellarators. Tokamaks are the dominant plasma confinement system and modeling based on SOC have provided a complementary approach to the understanding of plasma behavior under fusion conditions. These studies have provided insights into key features of toroidally confined plasmas, e.g., the existence of critical temperature gradients above which the transport rates increase drastically. The SOC models address the transport properties from a more general approach, compared to those based on turbulence arising from specific plasma instabilities, and provide a better framework for modeling features such as superdiffusion. The studies of space and laboratory plasmas as nonequilibrium systems have been motivated by features such as scaling and critical behavior, and have provided new insights by highlighting the properties that are common with other systems.

Experiences on developing E-government solutions have given a set of evidences that policy makers can profit in order to avoid poor results or to adopt best practices. Complexities on such solutions involve several considerations that should be managed using multiple variables related to different dimensions including political, economic, social, administrative and technological ones. Integrating theoretical principles from Public Value, Public Policies and Multidimensional Actor Model, could derive on a particular approach for the design of policies where E-government supports a political goal. Some cases are referred for illustrate this approach.

Landscape heterogeneity can often be represented as a series of discrete habitat or resource patches surrounded by a matrix of non-habitat. Understanding how animals move in such networks of patches is important for many theoretical and applied questions. The probability of going from one patch to another is affected in a non-trivial way by the characteristics and location of other patches in the network. Nearby patches can compete as possible destinations, and a particular patch can be shadowed by neighboring patches. We present a way to account for the effects of the spatial configuration of patches in models of space use where individuals alternate between spending time in a patch and moving to other patches in the network. The approach is based on the original derivation of Ovaskainen and Cornell (J Appl Probab 40:557–580, 2003) for a diffusion model that considered all possible ways in which an individual leaving a particular patch can eventually reach another patch before dying or leaving the patch network. By replacing the theoretical results of Ovaskainen and Cornell by other appropriate functions, we provide generality and thus make their approach useful in contexts where diffusion is not a good approximation of movement. Furthermore, we provide ways to estimate time spent in the non-habitat matrix when going from patch to patch and implement a method to incorporate the effect of the history of previous visits on future patch use. We present an MCMC way to fit these models to data and illustrate the approach with both simulated data and data from sheep moving among seasonally flooded meadows in northern Patagonia.Supplementary materials accompanying this paper appear online.